Source36氪•Stalecollected in 25h
xAI's Grok V9-Medium Model Training Completed
New 1.5T foundation model from xAI with heavy coding data integration arriving in weeks.
30-Second TL;DR
What Changed
Grok V9-Medium (1.5T) foundation model training is complete.
Why It Matters
The integration of Cursor data suggests a strong focus on coding capabilities, positioning Grok as a more competitive tool for developers.
What To Do Next
Prepare to benchmark Grok V9-Medium against current coding assistants once released to evaluate its performance on real-world development tasks.
Who should care:Developers & AI Engineers
Key Points
- •Grok V9-Medium (1.5T) foundation model training is complete.
- •Training data includes a large volume of Cursor-sourced coding data.
- •Official release is scheduled within 2 to 3 weeks following upcoming RL phases.
Deep Insight
Background and context from public sources — not the original article. 17 sources cited.
Enhanced Key Takeaways
- •The Grok V9-Medium model, with 1.5 trillion parameters, is three times larger than its predecessor, the v8-small model (0.5T parameters), which currently handles all Grok production traffic.
- •Elon Musk previously acknowledged that the v8-small model suffered from deficiencies in training data quality, comprehensiveness, and balance, which the V9-Medium aims to rectify.
- •Grok V9-Medium has been specifically optimized for NVIDIA Blackwell architecture GPUs, indicating a focus on leveraging cutting-edge hardware for performance.
- •The substantial incorporation of Cursor-sourced coding data is intended to significantly enhance Grok's capabilities in complex programming tasks, positioning it as an 'AI engineer' within the developer ecosystem.
- •Following the completion of training, the model is currently undergoing supervised fine-tuning, with reinforcement learning scheduled to commence in the coming days before its public release.
Competitor Analysis
Parameter Count
- Grok V9-Medium (Expected)
- 1.5T
- Grok 4.3 (Current)
- N/A (Grok 4 family)
- Claude Opus 4.7 (April 2026)
- N/A
- GPT-5.5 (April 2026)
- N/A
- Gemini 2.5 Pro (2026)
- N/A
Primary Focus
- Grok V9-Medium (Expected)
- Complex Programming, AI Engineer
- Grok 4.3 (Current)
- Real-time research, social media, X integration
- Claude Opus 4.7 (April 2026)
- Coding, long-horizon agent work
- GPT-5.5 (April 2026)
- Agentic workflows, multimodal tasks
- Gemini 2.5 Pro (2026)
- Google Workspace, Android, multimodal
SWE-bench Verified
- Grok V9-Medium (Expected)
- Expected significant improvement
- Grok 4.3 (Current)
- N/A (Grok 4 at 75%)
- Claude Opus 4.7 (April 2026)
- 87.6%
- GPT-5.5 (April 2026)
- 74.9% (GPT-5)
- Gemini 2.5 Pro (2026)
- N/A
Context Window
- Grok V9-Medium (Expected)
- N/A
- Grok 4.3 (Current)
- 1M tokens (Grok 4.3)
- Claude Opus 4.7 (April 2026)
- 1M tokens
- GPT-5.5 (April 2026)
- 1M tokens
- Gemini 2.5 Pro (2026)
- 1M tokens
GPU Optimization
- Grok V9-Medium (Expected)
- NVIDIA Blackwell architecture
- Grok 4.3 (Current)
- N/A
- Claude Opus 4.7 (April 2026)
- N/A
- GPT-5.5 (April 2026)
- N/A
- Gemini 2.5 Pro (2026)
- N/A
Pricing (API/Subscription)
- Grok V9-Medium (Expected)
- N/A (Grok 4.3 Beta: $300/month SuperGrok Heavy tier)
- Grok 4.3 (Current)
- $30/mo SuperGrok (Grok 4.3 Beta)
- Claude Opus 4.7 (April 2026)
- $20/mo Pro
- GPT-5.5 (April 2026)
- Free (ads) / $20/mo Plus
- Gemini 2.5 Pro (2026)
- Free / $20/mo Advanced
| Feature/Model | Grok V9-Medium (Expected) | Grok 4.3 (Current) | Claude Opus 4.7 (April 2026) | GPT-5.5 (April 2026) | Gemini 2.5 Pro (2026) |
|---|---|---|---|---|---|
| Parameter Count | 1.5T | N/A (Grok 4 family) | N/A | N/A | N/A |
| Primary Focus | Complex Programming, AI Engineer | Real-time research, social media, X integration | Coding, long-horizon agent work | Agentic workflows, multimodal tasks | Google Workspace, Android, multimodal |
| SWE-bench Verified | Expected significant improvement | N/A (Grok 4 at 75%) | 87.6% | 74.9% (GPT-5) | N/A |
| Context Window | N/A | 1M tokens (Grok 4.3) | 1M tokens | 1M tokens | 1M tokens |
| GPU Optimization | NVIDIA Blackwell architecture | N/A | N/A | N/A | N/A |
| Pricing (API/Subscription) | N/A (Grok 4.3 Beta: $300/month SuperGrok Heavy tier) | $30/mo SuperGrok (Grok 4.3 Beta) | $20/mo Pro | Free (ads) / $20/mo Plus | Free / $20/mo Advanced |
Technical Deep Dive
- Parameter Scale: Grok V9-Medium is a 1.5 trillion parameter foundation model.
- GPU Optimization: The model has been specifically optimized for NVIDIA Blackwell architecture GPUs.
- Training Data Focus: Incorporates a large volume of Cursor-sourced coding data, aiming for enhanced performance in complex programming tasks.
- Development Stages: Currently in the supervised fine-tuning phase, with reinforcement learning to follow before public release.
- Predecessor Comparison: It is three times the size of the previous v8-small model (0.5T parameters) that currently serves Grok's production traffic.
- Training Infrastructure (Historical): Earlier Grok models like Grok-3 were trained on the Colossus supercomputer cluster, which xAI stated utilized over 100,000 NVIDIA H100 GPUs.
- Architectural Basis (Historical): Grok-1, an earlier model, was a 314-billion-parameter Mixture-of-Experts (MoE) Transformer with 64 layers, 48 attention heads, an embedding dimension of 6,144, and an 8,192-token context window.
- Software Stack (Historical): xAI's training stack includes a JAX-based modeling and training layer, a Rust control plane for orchestration, and a Kubernetes substrate for scheduling.
Future ImplicationsAI analysis grounded in cited sources
Grok V9-Medium will significantly elevate xAI's standing in the AI coding assistant market.
The explicit focus on integrating extensive Cursor coding data and Elon Musk's statements about 'much better coding' capabilities suggest a direct challenge to established coding AI leaders.
The optimization for NVIDIA Blackwell GPUs indicates xAI's commitment to high-performance, next-generation AI infrastructure.
Early adoption and optimization for advanced GPU architectures like Blackwell suggest xAI is preparing for increasingly demanding AI workloads and larger models.
The planned open-sourcing of the 0.5T parameter model (v8-small) could accelerate broader developer engagement with xAI's ecosystem.
Making a capable, albeit smaller, model openly available can foster community contributions, drive innovation, and increase adoption of xAI's technology.
Timeline
2023-11
Grok-0 (33B parameters) launched as xAI's prototype language model.
2024-03
Grok-1 (314B parameters, Mixture-of-Experts architecture) released and open-sourced.
2024-08
Grok-2 and Grok-2 mini introduced, featuring enhanced reasoning and image generation capabilities.
2025-02
Grok 3 released, reportedly trained on the Colossus supercomputer cluster.
2025-07
Grok 4, a further iteration in the model family, was released.
2026-05-25
Grok V9-Medium (1.5T) foundation model training completed, with public release expected in 2-3 weeks.
- 2023-11Grok-0 (33B parameters) launched as xAI's prototype language model.
- 2024-03Grok-1 (314B parameters, Mixture-of-Experts architecture) released and open-sourced.
- 2024-08Grok-2 and Grok-2 mini introduced, featuring enhanced reasoning and image generation capabilities.
- 2025-02Grok 3 released, reportedly trained on the Colossus supercomputer cluster.
- 2025-07Grok 4, a further iteration in the model family, was released.
- 2026-05-25Grok V9-Medium (1.5T) foundation model training completed, with public release expected in 2-3 weeks.
Sources (17)
Factual claims are grounded in the sources below. Forward-looking analysis is AI-generated interpretation.
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